Fig. 6: Architecture of the deep learning model.
From: Enhancing self-management in type 1 diabetes with wearables and deep learning
A stack of bidirectional RNN (Bi-RNN) and RNN with GRU cells is used to extract hidden representations from the input multivariate time series. With the weighted state vector by attention layer, the evidential output computes glucose predictions along with model uncertainty.